Evidence map›Paper›PMID 27853512›Full record

ArticleF1000Research2016

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

Tanja Muetze, Ivan H Goenawan, Heather L Wiencko, Manuel Bernal-Llinares, Kenneth Bryan, David J Lynn

Open access · goldAbstract read
In one paragraph

Article in F1000Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Internal control of brain networks via sparse feedback.AIChE journal. American Institute of Chemical Engineers · 2023
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Bioinformatic analysis of differential expression and core GENEs in breast cancer.International journal of clinical and experimental pathology · 2018
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 3 countries.

Tanja MuetzeEMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
Ivan H GoenawanEMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
Heather L WienckoAnimal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Meath, Ireland.
Manuel Bernal-LlinaresEMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
Kenneth BryanEMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia.
David J LynnEMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia; School of Medicine, Flinders University, Bedford Park, Australia.
EMBL Australia · AUFlinders University · AUTeagasc - The Irish Agriculture and Food Development Authority · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such AVAILABILITY: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

Indexed as

CHATcontextual hub analysisgene expression datahubshypergeometric testNetwork analysis

Identifiers

PMID27853512
PMCPMC5105880
OpenAlexW2477204122

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.